Convex environmental contours

Abstract

Environmental contours are widely used as a basis for e.g., ship design, especially in early design phases. The traditional approach to such contours is based on the well-known Rosenblatt transformation. Here we focus on convex contours estimated using Monte Carlo methods and establish a rigorous mathematical foundation for such contours. In the present paper we also present an improved simulation procedure based on importance sampling. In particular, we show how this procedure can be extended to cases with omission factors and where the joint distribution of the environmental variables is a discrete mixture. It is well-known that contours constructed using Monte Carlo simulation typically have certain irregularities. In particular, the sets bounded by the estimated contours appear to be convex. However, when the curves are investigated more closely, they include a large number of small loops. In the present paper we provide a precise condition for convexity, and propose a smoothing method which can be used to eliminate the loops. The methods are illustrated by a numerical example.